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Criterion
How Might We
Innovation
How Might We
Paper illustration for Flywheel.
Growth
Flywheel
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
With a stuck problem carrying many implicit assumptions, the method translates observations into open, workable questions. It sharpens the problem frame without pre-thinking the solution, turning frustration or fuzziness into a search space with clear direction.Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
LowMediumHighLow
Timedifferent
30–45 min60-120 min1-4 Wochen1-5 Tage
Participantsdifferent
1-103-81-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshopAsyncAsync
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsFlywheel Map, Friction Points, Growth Levers, Experiment BacklogExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
FramingOpportunityIdeationQuestions
GrowthRetentionConversion
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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